Camtree Digital Library

Recent Submissions

  • PublicationOpen Access
    From Correction to Conversation: Enhancing Mathematical Understanding through Dialogic Questioning in a UK Classroom
    (2026) Liang, Renxuan
    Context: The study was conducted during an internship at Comberton Village College in the UK, where the researcher, a pre-service mathematics teacher from China, observed and participated in mathematics teaching. The focus was on employing dialogic questioning strategies to facilitate student understanding in mathematics, informed by prior training in dialogic pedagogy at Beijing Normal University and the use of a structured tool known as the Think-Talk Toolbox (TTT). Aims: The primary aim of the research was to determine how questioning strategies, particularly through the use of the question "How did you get that?" and the "Justifying" and "Guiding" strategies from the TTT, could enhance students' ability to identify their mistakes, deepen their understanding of mathematical concepts, and improve their engagement in classroom discussions. Methods: The inquiry involved systematic implementation of dialogic questioning during mathematics practice sessions, with a focus on creating a safe environment for student dialogue. Data were collected through various means including dialogue records, student work samples, teacher feedback, and self-reflection notes. A thematic analysis was then conducted to identify patterns and themes in student responses and the effectiveness of the guiding strategies employed. Findings: The findings showed diverse types of student responses to the questioning strategies, categorized into proactive, perplexed, and silent/resistant. The effective dialogue processes included using analogies from correctly solved problems and probing students' thought processes through follow-up questions. Increased student engagement was noted, with some previously reticent students becoming more participative. Nonetheless, obstacles such as language issues and time constraints affected the efficacy of the guidance provided. Implications: The study offers insights into the potential of dialogic questioning to enhance student engagement and understanding in mathematics education. Other educators might observe the benefits of replacing direct corrections with inquiries that encourage student reasoning. The findings underscore the value of maintaining a supportive and conversational classroom environment, recognizing errors as integral to the learning process and facilitating student ownership of their mathematical reasoning.
  • PublicationOpen Access
    Using the T-SEDA dialogic approach in ‘Introduction to Teaching Profession’ classes in Nigerian Higher Education
    (Camtree: the Cambridge Teacher Research Exchange, 2026) Sulyman, Abdulganiy
    Background and purpose: This study investigated the use of Toolkit for Systematic Educational Dialogue Analysis (T-SEDA) in the Nigerian higher education. The researcher observed in his class of adult learners that dialogue was poor and usually between the teacher and the learners, not among learners. The implication of this dialogic structure was that there was very little sharing of ideas and experiences among the learners. Aims: The aim of this study was to promote higher levels of dialogue among learners and enhance their reasoning and learning using the Toolkit for Systematic Educational Dialogue Analysis (T-SEDA). Design or methodology: The participants were the students of higher education in Nigeria. The inquiry context was the classroom in an ‘Introduction to Teaching Profession’ course. Self-audit and live coding observation were used to collect data. Analysis of baseline data and post-intervention data was done using Toolkit for Systematic Educational Dialogue Analysis (T-SEDA) coding scheme. At the intervention stage, the researcher exposed the learners to the concepts of educational dialogue including meaning, importance, dialogic moves, importance of learner-learner dialogue, and ground rules. Findings: The results gathered after the intervention demonstrated that students engaged more with one another and made more use of dialogic talk moves. Conclusions, originality, value and implications: It was concluded that students need to be exposed to T-SEDA dialogic approach or educational dialogue in order to improve their exchange of knowledge and ideas. This study suggests the value of encouraging educational dialogue and dialogic approaches in pedagogy in Nigerian education; the use of T-SEDA as a guide, and adoption of dialogic approach in research.
  • PublicationOpen Access
    The integration of Generative AI in the design search process
    (2026) Xu, Jeffrey; Sim, Clarice
    Context: The integration of Generative AI in educational practices has been rapidly evolving, particularly within design programs. Institutions like Singapore Polytechnic have begun leveraging generative AI tools, such as MidJourney and DALL·E, reshaping how students approach ideation, research, and creativity in a technology-driven environment. Aims: This study aims to explore the impact of a generative AI-assisted search workflow on design students' research and ideation processes. Specifically, it investigates how this integration affects students’ design vocabulary, variation in visual references, ability to justify visual choices, and overall design quality, guided by Puentedura’s SAMR model, particularly at the Modification level. Methods: The case study involved 45 second-year Visual Communication and Motion Design students. Data were collected through content analysis of submitted work, student and lecturer interviews, and assessment rubrics spanning five design briefs. A comparative analysis was made between students' abilities before and after exposure to the generative AI search methodology, with a focus on four specific research questions. Findings: Results indicated that higher readiness students experienced a slight expansion in their design vocabulary and variation in visual references. However, both high- and low-readiness groups struggled to adopt a broader range of visual references, revealing a tendency to rely on traditional search methods alongside AI. Students' abilities to justify their design choices and the overall quality of final designs showed minimal improvement, with many relying on AI-generated content without critical assessment or integration into their creative processes. Implications: The findings suggest that while generative AI can enhance ideation speed, it often does not deepen critical design reasoning or vocabulary development. The study highlights the need for structured frameworks that promote deeper engagement with AI outputs and a more diverse approach to research, suggesting that exposure to technology should be accompanied by explicit instruction in design principles and critical evaluation techniques to ensure meaningful learning outcomes.
  • PublicationOpen Access
    AI-Driven Teaching Innovation: A Practical Exploration of the Programming Internship and Image Processing Undergraduate Programs
    (2026) Yang, Shuai
    Background: With the rapid advancement of AI, integrating AI tools into higher education has become a transformative trend. As a teacher teaching two undergraduate courses: Practice of Programming and Image Processing, I leveraged AI to enhance course design and pedagogy, addressing the growing demand for AI learning among students. Problems, Challenges, or Opportunities Addressed: The innovation tackled: (1) Outdated programming course lacking AI relevance; (2) Limited student engagement in traditional image processing courses; (3) The need to equip students with practical AI skills. AI integration presented opportunities to modernize content, improve interactivity, and foster interdisciplinary competencies. Methods for Development and Evaluation: For Practice of Programming, Python replaced C++ for AI alignment, and DeepSeek assisted in creating interactive coding examples (e.g., a mini-game); for Image Processing, AI tools (e.g., Photoshop, HuggingFace) and deep learning techniques (e.g., diffusion models) were embedded into lectures and assignments. Student feedback and project outcomes were analysed to evaluate effectiveness. Key Findings and Outcomes: Students demonstrated improved engagement and creativity, especially in AI-driven projects. AI tools streamlined instructor workflows (e.g., generating teaching materials via DeepSeek). The courses successfully bridged foundational knowledge and cutting-edge AI applications. Impact on Teaching Practice: The innovation reinforced the role of AI as both a pedagogical aid and a core skill for students. It highlighted the need for educators to continuously adapt courses and embrace AI tools to enhance learning outcomes and career readiness.
  • PublicationOpen Access
    AI-empowered intangible cultural heritage activation: innovative practice in higher education to build a "dual-core-driven" smart teaching system
    (2026) Wang, Hei; Liu, Yipin; Ying, Li
    Background: Higher education urgently needs to move from passive adoption of AI tools to proactive exploration. Focusing on the course Installation Art and Environmental Facilities A at Tianjin University, we integrate Intangible Cultural Heritage (ICH) with generative AI to cultivate students’ cultural confidence and computational creativity. Challenges & Opportunities: Traditional ICH education suffers from static content, low interactivity, and limited interdisciplinary integration. AI offers generative power, yet risks cultural dilution and ethical misuse. Method: We developed the “dual-core” system: (1) an 8848.86 automated design platform that embeds 14 textbooks and 81 papers into a dynamic knowledge graph; (2) a “five-step three-state” pedagogical model (resource preparation → content design → classroom implementation → assessment → auxiliary support). Tools included MidJourney, Stable Diffusion, and Doubao Vision Model. Data-driven assessment used radar charts (cultural, technical, social dimensions). Findings: Design cycle shortened from 4 weeks to 6 days (300 % efficiency gain); award rate rose from 20 % (2020) to 99 % (2024). Cultural recognizability increased 55%; 89% of under-prepared students improved significantly. The system has been adopted by 20 universities, benefiting 5000+ students. Impact on Teaching: Instructors shifted from knowledge transmitters to learning architects, orchestrating AI-human synergy and ethical reflection. A replicable paradigm for AI-enhanced design education has been established.

Communities in Camtree Digital Library

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  • Supported by the Sixth Form Colleges Association and the Huish Centre for Practitioner Development, this is a space for research focusing on the unique 16-19 age range, conducted in sixth form colleges by sixth form staff.
  • Cambridge University Press and Assessment's International Education group
  • Camden Learning is a partnership between Camden Schools and Camden Council. It brings education practitioners together, to share expertise, drive improvement and achieve excellent practice.
  • Camtree is the Cambridge Teacher Research Exchange. This community contains peer-reviewed reports of close-to-practice research submitted to Camtree by teacher-researchers who are not associated with another Camtree partner or domain.
  • Research from the College of Education for the Future, part of Beijing Normal University at Zhuhai